Automatic segmentation of MR brain images in multiple sclerosis patients. - Ramesh T. V. Avula; Bradley J. Erickson (Image Processing, 1996)

Integration of PACS image display with an electronic medical record. - Bradley J. Erickson; Dale G. Gehring; William J. Ryan (Image Processing, 1997)

Clinical evaluation of wavelet compression of digitized chest x-rays. - Bradley J. Erickson; Armando Manduca; Kenneth R. Persons (Image Processing, 1997)

Histogram transformation for improved compression of CT images. - Armando Manduca; Bradley J. Erickson; Kenneth R. Persons; Patrice M. Palisson (Image Processing, 1997)

Evaluation of irreversible compression of digitized posterior-anterior chest radiographs. - Bradley James Erickson; Armando Manduca; Kenneth R. Persons; Frank Earnest; Thomas E. Hartman; Gordon F. Harms; Larry R. Brown (J. Digit. Imaging, 1997)

An algorithm for automatic segmentation and classification of magnetic resonance brain images. - Bradley James Erickson; Ramesh T. V. Avula (J. Digit. Imaging, 1998)

Ultrasound grayscale image compression with JPEG and wavelet techniques. - Kenneth R. Persons; Patrice Palisson; Armando Manduca; William J. Charboneau; E. Meredith James; Nicholas T. Charboneau; Nicholas J. Hangiandreou; Bradley James Erickson (J. Digit. Imaging, 2000)

Initial evaluation of a continuous speech recognition program for radiology. - Kalpana M. Kanal; Nicholas J. Hangiandreou; Anne-Marie Sykes; H. E. Eklund; P. A. Araoz; J. A. Leon; Bradley James Erickson (J. Digit. Imaging, 2001)

Irreversible Compression of Medical Images. - Bradley James Erickson (J. Digit. Imaging, 2002)

Computer-Aided Detection and Diagnosis at the Start of the Third Millennium. - Bradley James Erickson; Brian J. Bartholmai (J. Digit. Imaging, 2002)

Semiautomated Quantitation of Carotid Artery Stenosis in Gadolinium-Bolus Magnetic Resonance Angiography. - Bradley James Erickson; Brian A. Cole; John Huston (J. Digit. Imaging, 2002)

Requirements for an Enterprise Digital Image Archive. - Bradley James Erickson; Kenneth R. Persons; Nicholas J. Hangiandreou; E. Meredith James; Christopher J. Hanna; Dale G. Gehring (J. Digit. Imaging, 2002)

Evaluation of Irreversible JPEG Compression for A Clinical Ultrasound Practice. - Kenneth R. Persons; Nicholas J. Hangiandreou; Nicholas T. Charboneau; J. Charboneau; E. Meredith James; Bruce R. Douglas; Ann P. Salmon; John M. Knudsen; Bradley James Erickson (J. Digit. Imaging, 2002)

Improved classification accuracy by feature extraction using genetic algorithms. - Julia Willamena Patriarche; Armando Manduca; Bradley J. Erickson (Image Processing, 2003)

Design and implementation of an Internet-based medical image viewing system. - Shawn P. Laird; Johnny S. Wong; William J. Schaller; Bradley James Erickson; Piet C. de Groen (J. Syst. Softw., 2003)

Addressing the Coming Radiology Crisis - The Society for Computer Applications in Radiology Transforming the Radiological Interpretation Process (TRIPTM) Initiative. - Katherine P. Andriole; Richard L. Morin; Ronald L. Arenson; John A. Carrino; Bradley James Erickson; Steven C. Horii; David W. Piraino; Bruce I. Reiner; J. Anthony Seibert; Eliot L. Siegel (J. Digit. Imaging, 2004)

SCAR R&D Symposium 2003: Comparing the Efficacy of 5-MP CRT Versus 3-MP LCD in the Evaluation of Interstitial Lung Disease. - Steve Langer; Brian J. Bartholmai; Kenneth A. Fetterly; Scott Harmsen; William J. Ryan; Bradley James Erickson; Katherine P. Andriole; John A. Carrino (J. Digit. Imaging, 2004)

A Review of the Automated Detection of Change in Serial Imaging Studies of the Brain. - Julia Willamena Patriarche; Bradley James Erickson (J. Digit. Imaging, 2004)

Real-Time Mutual-Information-Based Linear Registration on the Cell Broadband Engine Processor. - Moriyoshi Ohara; Hangu Yeo; Frank Savino; Giridharan Iyengar; Leiguang Gong; Hiroshi Inoue; Hideaki Komatsu; Vadim Sheinin; Shahrokh Daijavad; Bradley J. Erickson (ISBI, 2007)

Effect of Automated Image Registration on Radiologist Interpretation. - Bradley James Erickson; Jayawant Mandrekar; Liqin Wang; Julia Willamena Patriarche; Brian J. Bartholmai; Christropher P. Wood; E. Paul Lindell; Anne-Marie Sykes; Gordon F. Harms; Rebecca M. Lindell; Katherine P. Andriole (J. Digit. Imaging, 2007)

Part 1. Automated Change Detection and Characterization in Serial MR Studies of Brain-Tumor Patients. - Julia Willamena Patriarche; Bradley James Erickson (J. Digit. Imaging, 2007)

Part 2. Automated Change Detection and Characterization Applied to Serial MR of Brain Tumors may Detect Progression Earlier than Human Experts. - Julia Willamena Patriarche; Bradley James Erickson (J. Digit. Imaging, 2007)

Optimizing Non-Local Means for Denoising Low Dose CT. - Zachary Kelm; Daniel J. Blezek; Brian J. Bartholmai; Bradley James Erickson (ISBI, 2009)

Cell Accelerated Cryoablation Simulation. - Daniel J. Blezek; David G. Carlson; Lionel Tim-Ee Cheng; Jared A. Christensen; Matthew R. Callstrom; Bradley James Erickson (Comput. Methods Programs Biomed., 2010)

Discerning Tumor Status from Unstructured MRI Reports - Completeness of Information in Existing Reports and Utility of Automated Natural Language Processing. - Lionel Tim-Ee Cheng; Jiaping Zheng; Guergana K. Savova; Bradley James Erickson (J. Digit. Imaging, 2010)

A Multicenter Observer Performance Study of 3D JPEG2000 Compression of Thin-Slice CT. - Bradley James Erickson; Elizabeth A. Krupinski; Katherine P. Andriole (J. Digit. Imaging, 2010)

Automated detection of Focal Cortical Dysplasia lesions on T1-weighted MRI using volume-based distributional features. - Chin-Ann Yang; Mostafa Kaveh; Bradley James Erickson (ISBI, 2011)

Experience with Importation of Electronic Images into the Medical Record from Physical Media. - Bradley James Erickson (J. Digit. Imaging, 2011)

Computer-Aided Detection of Intracranial Aneurysms in MR Angiography. - Xiaojiang Yang; Daniel J. Blezek; Lionel Tim-Ee Cheng; William J. Ryan; David F. Kallmes; Bradley James Erickson (J. Digit. Imaging, 2011)

Liver segmentation using structured sparse representations. - Vimal Singh; Dan Wang 006; Ahmed H. Tewfik; Bradley J. Erickson (ICASSP, 2012)

Cluster-based differential features to improve detection accuracy of focal cortical dysplasia. - Chin-Ann Yang; Mostafa Kaveh; Bradley J. Erickson (Computer-Aided Diagnosis, 2012)

Whitepapers on Imaging Infrastructure for Research - Part 1: General Workflow Considerations. - Bradley James Erickson; Tony Pan; Daniel S. Marcus (J. Digit. Imaging, 2012)

Imaging Infrastructure for Research. Part 2. Data Management Practices. - Daniel S. Marcus; Bradley James Erickson; Tony Pan (J. Digit. Imaging, 2012)

Whitepapers on Imaging Infrastructure for Research Part Three: Security and Privacy. - Tony Pan; Bradley James Erickson; Daniel S. Marcus (J. Digit. Imaging, 2012)

Standards for Business Analytics and Departmental Workflow. - Bradley James Erickson; Christopher Meenan; Steve Langer (J. Digit. Imaging, 2013)

Towards a More Cloud-Friendly Medical Imaging Applications Architecture: A Modest Proposal. - Steve G. Langer; Kenneth R. Persons; Bradley James Erickson; Daniel J. Blezek (J. Digit. Imaging, 2013)

Effects of Wireless Signal Attenuation on Robot Team Performance. - Briana Wellman; Bradley J. Erickson; Tommy Suriel; Kamala Mayo; Tajh Phifer; Kriti Acharya (FLAIRS, 2014)

CT image noise reduction using rotational-invariant feature in Stockwell transform. - Jian Su; Zhoubo Li; Lifeng Yu; Joshua D. Warner; Daniel J. Blezek; Bradley J. Erickson (Image Processing, 2014)

Web based tools for visualizing imaging data and development of XNATView, a zero footprint image viewer. - David A. Gutman; William D. Dunn; Jake Cobb; Richard Martin Stoner; Jayashree Kalpathy-Cramer; Bradley J. Erickson (Frontiers Neuroinformatics, 2014)

DEWEY: The DICOM-Enabled Workflow Engine System. - Bradley James Erickson; Steve G. Langer; Daniel J. Blezek; William J. Ryan; Todd French (J. Digit. Imaging, 2014)

Supervised Segmentation of Polycystic Kidneys: a New Application for Stereology Data. - Joshua D. Warner; Maria V. Irazabal; Ganapathy Krishnamurthi; Bernard F. King; Vicente E. Torres; Bradley J. Erickson (J. Digit. Imaging, 2014)

Temporal Annotation in the Clinical Domain. - William F. Styler IV; Steven Bethard; Sean Finan; Martha Palmer; Sameer Pradhan; Piet C. de Groen; Bradley James Erickson; Timothy Miller 002; Chen Lin 002; Guergana K. Savova; James Pustejovsky (Trans. Assoc. Comput. Linguistics, 2014)

The Best of Imaging Informatics Research 2015. - Charles E. Kahn; Bradley J. Erickson (AMIA, 2015)

The RSNA Image Sharing Network. - Steve G. Langer; Wyatt M. Tellis; Chris Carr; Mark Daly; Bradley James Erickson; David S. Mendelson; S. Moore; J. Perry; K. Shastri; Max Warnock; W. Zhu (J. Digit. Imaging, 2015)

Predicting 1p19q Chromosomal Deletion of Low-Grade Gliomas from MR Images using Deep Learning. - Zeynettin Akkus; Issa Ali; Jirí Sedlár; Timothy L. Kline; Jay P. Agrawal; Ian F. Parney; Caterina Giannini; Bradley J. Erickson (CoRR, 2016)

Predicting Deletion of Chromosomal Arms 1p/19q in Low-Grade Gliomas from MR Images Using Machine Intelligence. - Zeynettin Akkus; Issa Ali; Jirí Sedlár; Jay P. Agrawal; Ian F. Parney; Caterina Giannini; Bradley J. Erickson (J. Digit. Imaging, 2017)

Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions. - Zeynettin Akkus; Alfiia Galimzianova; Assaf Hoogi; Daniel L. Rubin; Bradley J. Erickson (J. Digit. Imaging, 2017)

Machine Learning: Discovering the Future of Medical Imaging. - Bradley J. Erickson (J. Digit. Imaging, 2017)

Toolkits and Libraries for Deep Learning. - Bradley J. Erickson; Panagiotis Korfiatis; Zeynettin Akkus; Timothy Kline; Kenneth Philbrick (J. Digit. Imaging, 2017)

Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys. - Timothy L. Kline; Panagiotis Korfiatis; Marie E. Edwards; Jaime D. Blais; Frank S. Czerwiec; Peter C. Harris; Bernard F. King; Vicente E. Torres; Bradley J. Erickson (J. Digit. Imaging, 2017)

Residual Deep Convolutional Neural Network Predicts MGMT Methylation Status. - Panagiotis Korfiatis; Timothy L. Kline; Daniel H. Lachance; Ian F. Parney; Jan C. Buckner; Bradley J. Erickson (J. Digit. Imaging, 2017)

Workflow Lexicons in Healthcare: Validation of the SWIM Lexicon. - Christopher Meenan; Bradley James Erickson; Nancy Knight; Jewel Fossett; Elizabeth Olsen; Prerna Mohod; Joseph Chen; Steve G. Langer (J. Digit. Imaging, 2017)

Evaluation of a deep learning architecture for MR imaging prediction of ATRX in glioma patients. - Panagiotis Korfiatis; Timothy L. Kline; Bradley J. Erickson (Computer-Aided Diagnosis, 2018)

Extraction of brain tissue from CT head images using fully convolutional neural networks. - Zeynettin Akkus; Petro M. Kostandy; Kenneth A. Philbrick; Bradley J. Erickson (Image Processing, 2018)

Differences Between Schizophrenic and Normal Subjects Using Network Properties from fMRI. - Youngoh Bae; Kunaraj Kumarasamy; Issa Ali; Panagiotis Korfiatis; Zeynettin Akkus; Bradley J. Erickson (J. Digit. Imaging, 2018)

Reduction of unnecessary thyroid biopsies using deep learning. - Zeynettin Akkus; Arunnit Boonrod; Mahfuzur R. Siddiquee; Kenneth A. Philbrick; Marius N. Stan; Regina M. Castro; Dana Erickson; Matthew R. Callstrom; Bradley J. Erickson (Image Processing, 2019)

Interactive segmentation of medical images through fully convolutional neural networks. - Tomas Sakinis; Fausto Milletari; Holger Roth; Panagiotis Korfiatis; Petro M. Kostandy; Kenneth Philbrick; Zeynettin Akkus; Ziyue Xu 001; Daguang Xu; Bradley J. Erickson (CoRR, 2019)

RIL-Contour: a Medical Imaging Dataset Annotation Tool for and with Deep Learning. - Kenneth A. Philbrick; Alexander D. Weston; Zeynettin Akkus; Timothy L. Kline; Panagiotis Korfiatis; Tomas Sakinis; Petro M. Kostandy; Arunnit Boonrod; Atefeh Zeinoddini; Naoki Takahashi; Bradley J. Erickson (J. Digit. Imaging, 2019)

Robust brain extraction tool for CT head images. - Zeynettin Akkus; Petro M. Kostandy; Kenneth A. Philbrick; Bradley J. Erickson (Neurocomputing, 2020)

MRI Brain Tumor Segmentation Using Deep Encoder-Decoder Convolutional Neural Networks. - Benjamin B. Yan; Yujia Wei; Jaidip Manikrao M. Jagtap; Mana Moassefi; Diana V. Vera Garcia; Yashbir Singh; Sanaz Vahdati; Shahriar Faghani; Bradley J. Erickson; Gian Marco Conte (BrainLes@MICCAI (2), 2021)

SOUP-GAN: Super-Resolution MRI Using Generative Adversarial Networks. - Kuan Zhang; Haoji Hu; Kenneth Philbrick; Gian Marco Conte; Joseph D. Sobek; Pouria Rouzrokh; Bradley J. Erickson (CoRR, 2021)

Deep Learning Improves the Temporal Reproducibility of Aortic Measurement. - Alex Bratt; Daniel J. Blezek; William J. Ryan; Kenneth A. Philbrick; Prabhakar Rajiah; Yasmeen K. Tandon; Lara A. Walkoff; Jason C. Cai; Emily N. Sheedy; Panagiotis Korfiatis; Eric E. Williamson; Bradley J. Erickson; et al. (J. Digit. Imaging, 2021)

Semantic Instance Segmentation of Kidney Cysts in MR Images: A Fully Automated 3D Approach Developed Through Active Learning. - Adriana V. Gregory; Deema A. Anaam; Andrew J. Vercnocke; Marie E. Edwards; Vicente E. Torres; Peter C. Harris; Bradley J. Erickson; Timothy L. Kline (J. Digit. Imaging, 2021)

Betti-Number Based Machine-Learning Classifier Frame-work for Predicting the Hepatic Decompensation in Patients with Primary Sclerosing Cholangitis. - Yashbir Singh; William Jons; Joseph D. Sobek; John E. Eaton; Bradley J. Erickson; Barrett J. Anderies; Jaidip Jagtap (CCWC, 2022)

Multitask Brain Tumor Inpainting with Diffusion Models: A Methodological Report. - Pouria Rouzrokh; Bardia Khosravi; Shahriar Faghani; Mana Moassefi; Sanaz Vahdati; Bradley J. Erickson (CoRR, 2022)

Genome-wide expression reveals potential biomarkers in breast cancer bone metastasis. - Yashbir Singh; Naidu Subbarao; Abhinav Jaimini; Quincy A. Hathaway; Amina Kunovac; Bradley James Erickson; Vishnu Swarup; Himanshu Narayan Singh (J. Integr. Bioinform., 2022)

Deep Neural Network for Cardiac Magnetic Resonance Image Segmentation. - David Chen 003; Huzefa M. Bhopalwala; Nakeya Dewaswala; Shivaram Poigai Arunachalam; Moein Enayati; Nasibeh Zanjirani Farahani; Kalyan Pasupathy; Sravani Lokineni; J. Martijn Bos; Peter A. Noseworthy; Reza Arsanjani; Bradley J. Erickson; et al. (J. Imaging, 2022)

Report of the Medical Image De-Identification (MIDI) Task Group - Best Practices and Recommendations. - David A. Clunie; Adam E. Flanders; Adam Taylor; Bradley James Erickson; Brian Bialecki; David Brundage; David Gutman; Fred W. Prior; J. Anthony Seibert; John H. Perry; Judy Wawira Gichoya; Justin S. Kirby; et al. (CoRR, 2023)

Synthetically Enhanced: Unveiling Synthetic Data's Potential in Medical Imaging Research. - Bardia Khosravi; Frank Li 005; Theo Dapamede; Pouria Rouzrokh; Cooper U. Gamble; Hari M. Trivedi; Cody C. Wyles; Andrew B. Sellergren; Saptarshi Purkayastha; Bradley J. Erickson; Judy W. Gichoya (CoRR, 2023)

MedYOLO: A Medical Image Object Detection Framework. - Joseph D. Sobek; Jose R. Medina Inojosa; Betsy J. Medina Inojosa; S. M. Rassoulinejad-Mousavi; Gian Marco Conte; Francisco Lopez-Jimenez; Bradley J. Erickson (CoRR, 2023)

Reproducibility of Deep Learning Algorithms Developed for Medical Imaging Analysis: A Systematic Review. - Mana Moassefi; Pouria Rouzrokh; Gian Marco Conte; Sanaz Vahdati; Tianyuan Fu; Aylin Tahmasebi; Mira Younis; Keyvan Farahani; Amilcare Gentili; Timothy Kline; Felipe C. Kitamura; Yuankai Huo; et al. (J. Imaging Inform. Medicine, 2023)

A Comparison of Three Different Deep Learning-Based Models to Predict the MGMT Promoter Methylation Status in Glioblastoma Using Brain MRI. - Shahriar Faghani; Bardia Khosravi; Mana Moassefi; Gian Marco Conte; Bradley J. Erickson (J. Digit. Imaging, 2023)

Effect of Dataset Size and Medical Image Modality on Convolutional Neural Network Model Performance for Automated Segmentation: A CT and MR Renal Tumor Imaging Study. - Harrison C. Gottlich; Adriana V. Gregory; Vidit Sharma; Abhinav Khanna; Amr U. Moustafa; Christine M. Lohse; Theodora A. Potretzke; Panagiotis Korfiatis; Aaron M. Potretzke; Aleksandar Denic; Andrew D. Rule; Naoki Takahashi; et al. (J. Digit. Imaging, 2023)

Few-shot biomedical image segmentation using diffusion models: Beyond image generation. - Bardia Khosravi; Pouria Rouzrokh; John P. Mickley; Shahriar Faghani; Kellen L. Mulford; Linjun Yang; A. Noelle Larson; Benjamin M. Howe; Bradley J. Erickson; Michael J. Taunton; Cody C. Wyles (Comput. Methods Programs Biomed., 2023)

Toward Clinically Trustworthy Deep Learning: Applying Conformal Prediction to Intracranial Hemorrhage Detection. - Cooper U. Gamble; Shahriar Faghani; Bradley J. Erickson (CoRR, 2024)

CONFLARE: CONFormal LArge language model REtrieval. - Pouria Rouzrokh; Shahriar Faghani; Cooper U. Gamble; Moein Shariatnia; Bradley J. Erickson (CoRR, 2024)

RadRotator: 3D Rotation of Radiographs with Diffusion Models. - Pouria Rouzrokh; Bardia Khosravi; Shahriar Faghani; Kellen L. Mulford; Michael J. Taunton; Bradley J. Erickson; Cody C. Wyles (CoRR, 2024)

HOPPR Medical-Grade Platform for Medical Imaging AI. - Kalina P. Slavkova; Melanie Traughber; Oliver Chen; Robert Bakos; Shayna Goldstein; Dan Harms; Bradley J. Erickson; Khan M. Siddiqui (CoRR, 2024)

Feasibility of Observing Cerebrovascular Disease Phenotypes with Smartphone Monitoring: Study Design Considerations for Real-World Studies. - Stephanie Zawada; Ali Ganjizadeh; Clint E. Hagen; Bart M. Demaerschalk; Bradley J. Erickson (Sensors, 2024)

A comparative analysis of privacy-preserving large language models for automated echocardiography report analysis. - Elham Mahmoudi; Sanaz Vahdati; Chieh-Ju Chao; Bardia Khosravi; Ajay Misra; Francisco Lopez-Jimenez; Bradley J. Erickson (J. Am. Medical Informatics Assoc., 2025)